The French critical zone initiative, called OZCAR (Observatoires de la Zone Critique-Application et Recherche or Critical Zone Observatories-Application and Research) is a National Research Infrastructure (RI). OZCAR-RI is a network of instrumented sites, bringing together 21 pre-existing research observatories monitoring different compartments of the zone situated between "the rock and the sky," the Earth's skin or critical zone (CZ), over the long term. These observatories are regionally based and have specific initial scientific questions, monitoring strategies, databases, and modeling activities. The diversity of OZCAR-RI observatories and sites is well representative of the heterogeneity of the CZ and of the scientific communities studying it. Despite this diversity, all OZCAR-RI sites share a main overarching mandate, which is to monitor, understand, and predict ("earthcast") the fluxes of water and matter of the Earth's near surface and how they will change in response to the "new climatic regime." The vision for OZCAR strategic development aims at designing an open infrastructure, building a national CZ community able to share a systemic representation of the CZ , and educating a new generation of scientists more apt to tackle the wicked problem of the Anthropocene. OZCAR articulates around: (i) a set of common scientific questions and cross-cutting scientific activities using the wealth of OZCAR-RI observatories, (ii) an ambitious instrumental development program, and (iii) a better interaction between data and models to integrate the different time and spatial scales. Internationally, OZCAR-RI aims at strengthening the CZ community by providing a model of organization for pre-existing observatories and by offering CZ instrumented sites. OZCAR is one of two French mirrors of the European Strategy Forum on Research Infrastructure (eLTER-ESFRI) project.

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International audienceIn coral islands, groundwater is a crucial freshwater resource for terrestrial life, including human water supply. Response of the freshwater lens to expected climate changes and subsequent vegetation alterations is quantified for Grande Glorieuse, a low-lying coral island in the Western Indian Ocean. Distributed models of recharge, evapotranspiration and saltwater phytotoxicity are integrated into a variable-density groundwater model to simulate the evolution of groundwater salinity. Model results are assessed against field observations including groundwater and geophys-ical measurements. Simulations show the major control currently exerted by the vegetation with regards to the lens morphology and the high sensitivity of the lens to climate alterations, impacting both quantity and salin-ity. Long-term changes in mean sea level and climatic conditions (rainfall and evapotranspiration) are predicted to be responsible for an average increase in salinity approaching 140 % (+8 kg m −3) when combined. In low-lying areas with high vegetation density, these changes top +300 % (+10 kg m −3). However, due to salinity increase and its phytotoxicity, it is shown that a corollary drop in vegetation activity can buffer the alteration of fresh groundwater. This illustrates the importance of accounting for vegetation dynamics to study groundwater in coral islands

International audienceThe prediction of landslide movement acceleration is a complex problem, among others identified for deep-seated landslides, and represents a crucial step for risk assessment. Within the scope of this problem, the objective of this paper is to explore a modelling method that enables the study of landslide function and facilitates displacement predictions based on a limited data set. An inverse modelling approach is proposed for predicting the temporal evolution of landslide movement based on rainfall and displacement velocities. Initially, the hydrogeology of the studied landslides was conceptualised based on correlative analyses. Subsequently, we applied an inverse model with a Gaussian-exponential transfer function to reproduce the displacements. This method was tested on the Grand Ilet (GI) and Mare-à-Poule-d'Eau (HB) landslides on Reunion Island in the Indian Ocean. We show that the behaviour of landslides can be modelled by inverse models with a bimodal transfer function using a Gaussian-exponential impulse response. The cumulative displacements over 7 years of modelling (2 years of calibration period for GI, and 4 years for HB) were reproduced with an RMSE above 0.9. The characteristics of the bimodal transfer function are directly related to the hydrogeological functioning demonstrated by the correlative analyses: the rapid reaction of a landslide can be associated with the effect of a preferential flow path on groundwater level variations. Thus, this study shows that the inverse model using a Gaussian-exponential transfer function is a powerful tool for predicting deep-seated landslide movements and for studying how they function. Beyond modelling displacements, our approach effectively demonstrates its ability to contribute relevant data for conceptualising the sliding mechanisms and hydrogeology of landslides